… But nobody can use it.
<div class="form-group shiny-input-container">
<label class="control-label" id="select-label" for="select">Select</label>
<div>
<select id="select" class="shiny-input-select"><option value="mpg" selected>mpg</option>
<option value="cyl">cyl</option>
<option value="disp">disp</option>
<option value="hp">hp</option>
<option value="drat">drat</option>
<option value="wt">wt</option>
<option value="qsec">qsec</option>
<option value="vs">vs</option>
<option value="am">am</option>
<option value="gear">gear</option>
<option value="carb">carb</option></select>
<script type="application/json" data-for="select" data-nonempty="">{"plugins":["selectize-plugin-a11y"]}</script>
</div>
</div>
You don’t need to write any HTML, CSS and JS (but you could 😈…)
inputId, variable.input[["variable"]] or input$variable.input is read only.renderTable, renderPlot, …data.tableOutput, plotOutput, …output is readonly.We consider the logistic model used to describe population growth.
\[ \frac{dN}{dt} = rN \left( 1 - \frac{N}{K} \right) \] whose solution is given by:
\[ N(t) = \frac{K}{1 + \left(\frac{K - N_0}{N_0}\right) e^{-rt}} \] Where:
N(t) is the population size at time t.K is the carrying capacity.r is the intrinsic growth rate.t=0.We define the following objective function, \(y_i\) being the observed data and \(f(x_i, \beta)\) the model predictions given a set of parameters \(\beta\):
\[ S(\beta) = \sum_{i=1}^{n} (y_i - f(x_i, \beta))^2 \] We want to minimize this ( represents the best parameters estimate):
\[ \hat{\beta} = \arg \min_{\beta} S(\beta) =\arg \min_{\beta} \sum_{i=1}^{n} (y_i - f(x_i, \beta))^2 \]